Fuchs, JohannesIsenberg, PetraBezerianos, AnastasiaMiller, MatthiasKeim, DanielTarini, Marco and Galin, Eric2019-05-052019-05-0520191017-4656https://doi.org/10.2312/eged.20191023https://diglib.eg.org:443/handle/10.2312/eged20191023We present EduClust, a visualization application for teaching clustering algorithms. EduClust is an online application that combines visualizations, interactions, and animations to facilitate the understanding and teaching of clustering steps, parameters, and procedures. Traditional classroom settings aim for cognitive processes like remembering and understanding. We designed EduClust for expanded educational objectives like applying and evaluating. Educators can use the tool in class to show the effect of different clustering parameters on various datasets while animating through each algorithm's steps, but also use the tool to prepare traditional teaching material quickly by exporting animations and images. Students, on the other hand, benefit from the ability to compare and contrast the influence of clustering parameters on different datasets, while seeing technical details such as pseudocode and step-by-step explanations.Theory of computationUnsupervised learning and clusteringApplied computingInteractive learning environments10.2312/eged.201910239-16